Distributed index searching in computing systems

ABSTRACT

Computer systems, devices, and associated methods of providing distributed index searching are disclosed herein. In one embodiment, a method includes receiving, at a database server, search terms included in a search query for content from a member and in response to receiving the search terms, determining a subset of the distributed indices to be searched in response to the search query based on the received search terms and one or more records of searching features on the database server. The method also includes providing the determined list of distributed indices to be searched based on the search terms in the search query.

BACKGROUND

Corporations, schools, charities, government entities, and other typesof organizations often deploy private computer networks commonlyreferred to as intranets. Such intranets can include servers, networkdevices, or other suitable devices under the control of an organization,or can include a web-based solution such as SharePoint®, Google Drive®,or computing platforms. Intranets can allow members of an organizationto securely share information within the enterprise. For example, anintranet can be configured to store, track, or otherwise manage internaldocuments of an organization. In contrast, the term “internet” typicallyrefers to public computer networks interconnecting individuals andorganizations. One such example is the Internet, which contains billionsinterconnected of computers worldwide based on the TCP/IP protocol.

SUMMARY

This Summary is provided to introduce a selection of concepts in asimplified form that are further described below in the DetailedDescription. This Summary is not intended to identify key features oressential features of the claimed subject matter, nor is it intended tobe used to limit the scope of the claimed subject matter.

Intranets can provide members of an organization ability to search forvarious types of content items within the organization. For example, anintranet can include one or more repositories that store emails,documents, videos, audios, webpages, or other suitable types of content.The intranet can also include a search engine that allows members of theorganization to search and retrieve any stored content. Such searchescan be based on, for example, keywords, alternate phrases, or othersuitable criteria. The search engine can then return a list of contentitems to the members as search results.

One challenge of facilitating searching and retrieval of content is theefforts involved in compiling and maintaining an index for the variouscontent items on the intranets. For example, certain intranets caninclude thousands of content servers containing different content items.To compile and update a master index that reference all content itemsacross such many content servers can involve a large amount of effortsand costs due to accuracy, latency, and other requirements. For example,changes in content items may require speedy update in the master indexto ensure accurate indexing of the content items. Compiling such masterindices is also not readily scalable because each content itemcorresponds to an entry in the master index. In addition, servers orother suitable components supporting the master index can be a singlepoint of failure for the entire searching and retrieval system.

One technique for addressing the foregoing challenges is to partitionthe master index into multiple distributed child indices (or “shards”).Instead of referencing a content item directly, the master index insteadreferences one of the child indices that in turn directly references thecontent item. During a search, the master index can identify a shardthat may contain the searched content item(s) and delegate searching andretrieval of the content item(s) to the shard(s) in a technique commonlyreferred to as “fan out”. Such a technique, however, still involve greatefforts in compiling, updating, and maintaining the references betweenthe master index and the child indices. For example, once a referencebetween a child index and a content item is established, changed, orremoved, the master index must be immediately updated accordingly inorder to ensure that any provided search data is accurate and “fresh.”

Several embodiments of the disclosed technology can address at leastsome of the foregoing challenges by providing (i) servers hostingdistributed indices (or shards) close to corresponding content items and(ii) a database server hosting a database containing records ofsearching features of the content items related to an organization,sub-organizations, groups of members, or individual members of theorganization. For example, such searching features can include topkeywords, query history, amount of searching or other activities in theorganization, sub-organizations, groups of members, and/or a member ofthe organization. Data of such searching features can be collectedperiodically from the individual servers hosting the distributed indicesusing a crawler or other suitable components and/or techniques.

In certain embodiments, a search request for content can be receivedfrom a member of the organization at a search engine containing recordsof searching history and/or other suitable types of profile informationregarding the member. The search engine can then transmit the searchrequest with corresponding search terms (e.g., “engineering doc”) andthe member's profile information to the database server containing therecords of searching features. The database server can then determine asubset of distributed indices to be searched based on the records of thesearching features, the profile information of the member, and/or thesearch terms included in the search request. In one example, thedatabase server can determine that the subset of distributed indices tobe searched only include indices related to the sub-organization (e.g.,“engineering department”) of the member. In other examples, the databaseserver can determine that the subset of distributed indices can includethose most searched in the organization, a sub-organization of theorganization, or a group of other members the member interacts mostwith. In other embodiments, the search engine can also supplement,subtract, or otherwise modify the subset of distributed indices basedon, for instance, the search history of the member or other suitableinformation.

The database server can then provide the determined subset ofdistributed indices to the search engine. In response, the search enginecan “fan out,” e.g., by requesting corresponding content servers hostingthe subset of distributed indices to conduct content item searches basedon the received searching request. The content servers can then performthe requested search based on keyword, alternate expression, or othersuitable searching techniques. The content servers can then providederived search results back to the search engine. The search engine canthen compile, organize, or otherwise process the received searchresults, and provide a list of content items to the member in responseto the search request.

Several embodiments of the disclosed technology can eliminate the largeamount of efforts involved in maintaining a master index of all contentitems on an intranet of an organization. Unlike massive master indices(e.g., gigabytes) that each include records of millions of content itemsor sub-indices, the database size of searching feature records can bequite small (e.g., kilobytes). The searching features do not aim tocapture all references of content items available. Instead, thesearching features aim to capture statistical or profile informationrelated to how such content items referenced in a distributed index havebeen searched. Several embodiments of the disclosed technology can thusbe scalable. Unlike techniques implementing master indices,modifications of references in a distributed index may not necessarilyincrease the database size of the searching features because searchingactivities of the modified references may be combined with existingsearching features. Thus, each distributed index can independentlycreate, update, or manage references to corresponding content itemswithout requiring immediate update in the database of the searchingfeatures.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic diagram illustrating a computing systemimplementing distributed index searching of content in accordance withembodiments of the disclosed technology.

FIGS. 2A-2C are schematic diagrams illustrating hardware/softwarecomponents of the computing system of FIG. 1 during a content searchoperations in accordance with embodiments of the disclosed technology.

FIG. 3 is a schematic diagram illustrating hardware/software componentsof a feature tracker suitable for the computing system of FIG. 1 inaccordance with embodiments of the disclosed technology.

FIGS. 4A-4B are example data schemas suitable for records of searchingfeatures in accordance with embodiments of the disclosed technology.

FIGS. 5A-5B are flowcharts illustrating various processes of providingdistributed index searching in accordance with embodiments of thedisclosed technology.

FIG. 6 is a flowchart illustrating a process of compiling a database ofsearching features in accordance with embodiments of the disclosedtechnology.

FIG. 7 is a computing device suitable for certain components of thecomputing system in FIG. 1.

DETAILED DESCRIPTION

Certain embodiments of systems, devices, components, modules, routines,data structures, and processes for distributed index searching in acomputer network are described below. In the following description,specific details of components are included to provide a thoroughunderstanding of certain embodiments of the disclosed technology. Aperson skilled in the relevant art will also understand that thetechnology can have additional embodiments. The technology can also bepracticed without several of the details of the embodiments describedbelow with reference to FIGS. 1-7.

As used herein, the term “content item” generally refers to an item ofinformation resource accessible via a computer network. For example, acontent item can include a document containing text, images, sounds,videos, or animations stored in a network repository and accessible viathe computer network. In another example, a content item can alsoinclude a website with one or more webpages accessible via the computernetwork. In additional examples, content items can include blog sites,discussion forums, electronic commerce sites, or other suitable types ofresources.

Also used herein, the term “distributed index” or “shard” generallyrefers to a partition of records in a database or search engine. Eachdistributed index or shard can be hosted and maintained on a separatecontent server. The individual shards can be implemented as horizontal,vertical, or other suitable partition of an overall index. In certainembodiments, one or more database records may be present in more thanone distributed indices. In other embodiments, a database record mayonly appear in a single distributed index.

As used herein, the term “searching features” generally refers tometadata, database records, or other suitable types of data containinginformation of content searching or interaction profiles related to anintranet, internet, or other suitable types of computing systems. In oneexample, the profiles can be compiled as database records based onsearching histories of an organization, a sub-organization, a group ofmembers, or individual members of the organization. For instance, aprofile record can contain top keywords searched, query history, amountof searching of an organization, sub-organization, groups of members, orindividual members of the organization on an intranet. In anotherexample, the profiles can also include database records compiled basedon interaction history of sub-organization, groups of members, orindividual members of an organization. For instance, another profilerecord can contain emails sent, comments received, or other suitabletypes of interactions between members over an intranet. Examplesdatabase records suitable for storing searching features are describedin more detail below with reference to FIGS. 4A-4B.

Intranets can provide members of an organization an ability to searchfor various types of content items within the organization. However,efforts involved in compiling, updating, and maintaining a distributedindex of the content items can quickly escalate to unsustainable levels.For example, to compile and update a master index that referencethousands or even millions content items can involve a large amount ofefforts and costs due to accuracy, latency, and other requirements.Several embodiments of the disclosed technology can address at leastsome of the foregoing challenge by maintaining a database containingrecords of searching features related to an organization,sub-organizations, groups of members, or individual members of theorganization, instead of a master index that references all contentitems or child indices hosted on content servers. During a search, asubset of content servers can be identified based on a search requestand the searching features in the database. The search request can thenbe fanned out to the subset of content servers to search distributedindices and retrieve suitable content items, as described in more detailbelow with reference to FIGS. 1-7.

FIG. 1 is a schematic diagram illustrating a computing system 100implementing personalized content suggestion in accordance withembodiments of the disclosed technology. As shown in FIG. 1, thecomputing system 100 can include a computer network 104 interconnectingclient devices 102, a search engine 106, a feature tracker 112, and oneor more content servers 118. In the illustrated embodiment, two contentservers 118 are shown for illustration purposes. In other embodiments,the computing system 100 can include three, four, or any suitable numberof content servers 118. The computer network 104 can include anorganization intranet, a social network, the Internet, or other suitabletypes of network.

The computing system 100 can also include a network repository 108operatively coupled to the content servers 118 and a network storage 114operatively coupled to the feature tracker 112. As shown in FIG. 1, thenetwork repository 108 can be configured to store records of contentitems 110 and corresponding distributed index 111 accessible via thecomputer network 104. The network storage 114 can be configured to storerecords of searching features 116 containing data representing searchingprofiles and interaction among the members 101 over the computer network104.

In the illustrated embodiment, computing system 100 can further includea search storage 109 operatively coupled to the search engine 106. Thesearch storage 109 can be configured to store records of member profile113. In certain examples, the member profile 113 can include emailaddress, organization hierarchy, interactions with other members 101,and content visit histories of a member 101. In other examples, themember profile 113 can also include sub-organization(s) the member 101belongs to, content browsing histories, or other suitable profileinformation related to a member 101. In other embodiments, the recordsof member profile 113 can be stored in the network storage 114 or one ormore of the network repositories 108.

Even though particular components and associated arrangements of thecomputing system 100 are shown in FIG. 1, in other embodiments, thecomputing system 100 can include additional and/or different components.For example, in certain embodiments, the network repository 108 and thenetwork storage 114 can be combined into a single physical or logicalstorage space. In other embodiments, the computing system 100 can alsoinclude caching servers, load balancers, or other suitable components.

The client devices 102 can individually include a computing device thatfacilitates access to the network repository 108 via the computernetwork 104 by members 101 (identified as first, second, and thirdmembers 101 a-101 c). For example, in the illustrative embodiment, thefirst client device 102 a includes a laptop computer. The second clientdevice 102 b includes a desktop computer. The third client device 102 cincludes a tablet computer. In other embodiments, the client devices 102can also include smartphones or other suitable computing devices. Eventhough three members 101 are shown in FIG. 1 for illustration purposes,in other embodiments, the computing system 100 can facilitate anysuitable number of members 101 access to the network repository 108 viathe computer network 104.

In certain embodiments, the search engine 106, the feature tracker 112,and the content servers 118 can each include one or more interconnectedcomputer servers, as shown in FIG. 1. In other embodiments, theforegoing components of the computing system 100 can each include acloud-based service hosted on one or more remote computing facilitiessuch as datacenters. In further embodiments, certain components (e.g.,the content servers 118) may be omitted from the computing system 100and be provided by external computing systems (not shown).

The content servers 118 can be configured to provide one or more contentitems 110 accessible by the members 101 via the computer network 104.For example, in one embodiment, the content servers 118 can beconfigured to provide an organization file management system that allowsthe members 101 to securely create, modify, delete, or otherwise processcontent items 110. In other embodiments, the content servers 118 canalso be configured to provide a social network website with webpagesthat allow the members 101 to post content items 110, comment on oneanother's content items 110, share and/or recommend content items 110with additional members 101, or perform other suitable actions.

The content servers 118 can also be configured to independently receive,store, catalog, or otherwise manage the content items 110 in thecorresponding network repository 108. As shown in FIG. 1, the contentservers 118 can individually compile, update, or maintain a distributedindex 111 of the content items 110 stored on or co-located with thecontent items 110 the corresponding content servers 118. The distributedindices 111 can include keywords, related words, or other suitablereferences that facilitate locating a particular content item 110. Forexample, the first content server 118′ can independently compile,update, and maintain a first distributed index 111′ for searching thefirst set of content items 110′ stored on the first network repository108′ operatively coupled to the first content server 118′. The secondcontent server 118′ can also independently compile, update, and maintaina second distributed index 111″ for searching the second set of contentitems 110″ stored on the second network repository 108″ operativelycoupled to the second content server 118″. As such, the firstdistributed index 118′ can include entries different than the seconddistributed index 118″. The content servers 118 can also be configuredto search the corresponding distributed indices 111 based on searchterms or other suitable information, as described in more below.

The feature tracker 112 can be configured to generate, update, orotherwise manage records of searching features (i) for an organizationutilizing the computer system 100 and (ii) among the individual members101 and one or more content items 110 stored in the network repositories108. For example, in one embodiment, the feature tracker 112 can recordinteractions between pairs of the members 101 via online postings,emails, phone calls, text messages, online chats, or other suitableinteractions. In another embodiment, the feature tracker 112 can alsorecord interactions between the individual members 101 and one or moreof the content items 110. Example interactions can include creating,editing, saving, viewing, commenting, or performing other suitableactions by the members 101 on the content items 110.

In further embodiments, the feature tracker 112 can also be configuredto record organizational positions, expertise, or other suitableinformation related to the individual members 101. In yet furtherembodiments, the feature tracker 112 can collect searching histories ofan organization, sub-organization, groups of members 101, or theindividual members 101 from the content servers 108 using a crawler orother suitable techniques. In yet other embodiments, the feature tracker112 can be configured to identify a list of content servers 118 to besearched based on the records of the searching features 116, asdescribed below. Certain hardware/software components suitable for thefeatures tracker 112 are described below with reference to FIGS. 2A-3.

The search engine 106 can be configured to provide a list of contentitems 110 in the network repositories 108 to the member 101 in responseto a search query 138 received from the member 101. In certainembodiments, the search engine 106 can be configured to receive a searchquery 138 from the member 101. The search query 138 can contain one ormore search terms (e.g., “engineering doc”). In response, in certainembodiments, the search engine 106 can be configured to transmit thereceived search query 138 and information in a record of member profile113 corresponding to the member 101 to the feature tracker 112.

In turn, the feature tracker 112 can identify a list of content servers118 and/or distributed indices 111 maintained on the content servers 118to be searched based on the searching features 116 stored in the networkstorage 114. The feature tracker 112 can then transmit the identifiedlist of content servers and/or distributed indices 111 to the searchengine 106, which in turn transmits one or more search requests to theidentified content server(s) 118 for searching corresponding distributedindices 111 based on the search terms in the search query 138. Thecontent server(s) 118 can then performed the requested searches andreturn a set of search results to the search engine 106 to be presentedto the member 101. In certain embodiments, the feature tracker 112 andthe search engine 106 can each include a standalone server or cluster ofservers in the computing system 100. In other embodiments, the featuretracker 112 and/or the search engine 106 can also be a computing servicedeployed in the computing system 100 on, for example, one or more of thecontent server(s) 118 or other suitable components. Various embodimentsof components and operations of the search engine 106, feature tracker112, and content servers 118 are discussed in more details below withreference to FIGS. 2A-2C.

FIGS. 2A-2C are schematic diagrams illustrating hardware/softwarecomponents of the search engine 106, feature tracker 112, and contentservers 118 of FIG. 1 during a search in accordance with embodiments ofthe disclosed technology. In the following description, certaincomponents of the computing system 100 are omitted from certain figuresfor clarity. For example, the content servers 110 are omitted in FIG.2A, and the feature tracker 112 is omitted from FIG. 2C.

In addition, in FIGS. 2A-2C and in other Figures herein, individualsoftware components, objects, classes, modules, and routines may be acomputer program, procedure, or process written as source code in C,C++, C#, Java, and/or other suitable programming languages. A componentmay include, without limitation, one or more modules, objects, classes,routines, properties, processes, threads, executables, libraries, orother components. Components may be in source or binary form. Componentsmay include aspects of source code before compilation (e.g., classes,properties, procedures, routines), compiled binary units (e.g.,libraries, executables), or artifacts instantiated and used at runtime(e.g., objects, processes, threads). In certain embodiments, the variouscomponents and modules described below can be implemented with actors.In other embodiments, generation of the application and/or relatedservices can also be implemented using monolithic applications,multi-tiered applications, or other suitable components.

Components within a system can take different forms within the system.As one example, a system comprising a first component, a secondcomponent and a third component can, without limitation, encompass asystem that has the first component being a property in source code, thesecond component being a binary compiled library, and the thirdcomponent being a thread created at runtime. The computer program,procedure, or process may be compiled into object, intermediate, ormachine code and presented for execution by one or more processors of apersonal computer, a network server, a laptop computer, a smartphone,and/or other suitable computing devices. Equally, components may includehardware circuitry.

A person of ordinary skill in the art would recognize that hardware maybe considered fossilized software, and software may be consideredliquefied hardware. As just one example, software instructions in acomponent may be burned to a Programmable Logic Array circuit, or may bedesigned as a hardware circuit with appropriate integrated circuits.Equally, hardware may be emulated by software. Various implementationsof source, intermediate, and/or object code and associated data may bestored in a computer memory that includes read-only memory,random-access memory, magnetic disk storage media, optical storagemedia, flash memory devices, and/or other suitable computer readablestorage media excluding propagated signals.

As shown in FIG. 2A, the search engine 106 can include an input/outputcomponent 152, a selection component 154, and a filter component 156operatively coupled to one another. Even though particular components ofthe search engine 106 are shown in FIG. 2A and other figures herein, inother embodiments, the search engine 106 can also include cachingcomponent, sorting component, database component, or other suitablecomponents. In further embodiments, the filter component 156 and/orother components may be omitted from the search engine 106.

The input/output component 152 can be configured to receive a searchquery 138 from a member 101 via a client device 102. In one embodiment,the search query 138 can include an input in a search box displayed on awebpage, for example, provided by one of the content servers 118 ofFIG. 1. In another embodiment, the search query 138 can include an inputin an address field of a browser, an express command from the member101, or other suitable types of user input from the member 101. Theinput/output component 152 can be configured to provide the receivedsearch query 138 to the selection component 154 for further processing.In certain embodiments, the input/output component 152 can include auser interface on, for example, a web browser. In other embodiments, theinput/output component 152 can include an application programminginterface or other suitable types of interface.

The selection component 154 can be configured to determine a list ofcontent servers 118 (FIG. 1) and/or corresponding distributed indices118 to search for content items based on the received search query 138.In certain embodiments, the selection component 152 can retrieve arecord of member profile 113 from the search storage 109 correspondingto the member 101. The selection component 154 can then transmit atleast a portion of the search query 138 and the member profile 113 tothe feature tracker 112. Upon receiving the search query 138 and themember profile 113, the feature tracker 112 can be configured todetermine a search list 140 containing identifications of contentservers 110 and/or corresponding distributed indices 118 based on thesearching features 116 stored in the network storage 116, as describedin more detail below with reference to FIG. 3. The feature tracker 112can then return the determined search list 140 to the search engine 106.

As shown in FIG. 2B, in certain embodiments, the selection component 154can transmit one or more search requests 142 to the content servers 118identified in the received search list 140 via the computer network 104(FIG. 1). In certain examples, the search requests 142 can contain datarepresenting the search terms in the search query 138 and an instructionto search the distributed indices 111 for content items 110 based on thesearch terms. In other examples, the search requests 142 can alsocontain a target size of search results, latency requirements, and/orother suitable information.

In other embodiments, the selection component 154 can modify the searchlist 140 before transmitting the search requests 142. For instance, theselection component 154 can supplement the search list 140 withadditional identifications of content servers 110 based on, inter alia,information contained in the member profile 113 of the member 101. Forexample, the selection component 154 can identify one or more contentservers 110 that contain distributed indices 118 that are frequentlysearched in response to previous search queries 138 from the member 101.In another example, the selection component 154 can identify one or morecontent servers 110 that contain distributed indices 118 correspondingto content items 110 the member 101 frequently interacted with. Infurther examples, the selection component 154 can also delete, modify,or otherwise adjust the search list 140.

As shown in FIG. 2C, the content servers 118 can then perform contentsearches using corresponding distributed indices 111 to locate relevantcontent items 110 corresponding to the search query 138. Upon completingthe requested content searches, the content servers 118 can provideindividual sets of search results 144 to the filter component 156 of thesearch engine 106. The filter component 156 can then be configured tosort, filter, combine, or otherwise aggregate the received sets ofsearch results 144 to generate overall search results 144″. Forinstance, the filter component 156 can rank and sort the received searchresults 144 based on relevance, data size, data type, or other suitablecriteria. The filter component 156 can then provide the overall searchresults 144″ to the client device 102 via the input/output component152.

Several embodiments of the computing system 100 described above caneliminate the large amount of efforts involved in maintaining a masterindex of all content items 110 accessible via the computer network 104(FIG. 1). Master indices can become massive (e.g., gigabytes) whenrecords of millions or even billions of content items are included. Incontrast, the size of the records of searching features 116 can be quitesmall (e.g., kilobytes) because the searching features 116 do not aim tocapture all references of content items 110 available on the computernetwork 104. Instead, the searching features 116 contain statistical orprofile information related to how the content items 110 referenced inthe distributed indices 111 have been searched.

The utilization of the searching features 116 instead of a master indexcan also allow improved scalability of the computer system 100. Unlikeusing master indices, modifications of references in a distributed index111 may not affect records of searching features 116 in a one-to-onefashion. Instead, in certain embodiments, the searching features 116capture how the references in the distributed index has been searched.Thus, a new addition to the distributed index 111 does not require animmediate update in the searching features 116. Instead, the searchingfeatures 116 may be updated when searching activities related to the newaddition has been detected.

FIG. 3 is a schematic diagram illustrating hardware/software componentsof a feature tracker 112 suitable for the computing system of FIG. 1 inaccordance with embodiments of the disclosed technology. As shown inFIG. 3, the feature tracker 112 can include a collection component 122and a search component 124 operatively coupled to one another. Thoughparticular components are shown in FIG. 3, in other embodiments, thefeature tracker 112 can also include interface components, databasecomponents, and/or other suitable components.

The collection component 122 can be configured to collect historical orstatistical information related to searching activities 130 on thecontent servers 110. In certain embodiments, the collection component122 can include a crawler configured to contact and collect searchinghistories, searching statistics, and/or other suitable information fromthe content servers 110 (FIG. 1) via the computer network 104 (FIG. 1).In other embodiments, the content servers 110 can be configured toprovide the collection component 122 with such information on a periodicor other suitable basis. In further embodiments, the collectioncomponent 122 can periodically receive such information from the contentservers and utilizing the crawler for periodic updates.

In certain embodiments, the collection component 122 can also beconfigured to receive organizational chart 132, interaction profiles134, and/or other suitable information related to individual members 101(FIG. 1). In one example, the organization chart 132 can identify one ormore peer members 101 related to a particular member 101. In anotherexample, the organization chart 132 can identify a group, department, orother suitable types of sub-organization a member 101 belongs to. Infurther examples, the interaction profiles 134 can include informationrelated to searching history/frequencies, communicationhistory/frequencies, or other suitable information related to a member101. In other embodiments, the foregoing information related to theindividual members 101 can be collected and compiled as member profiled113 (FIG. 1) by the search engine 106.

The collection component 122 can also be configured to compile, update,or otherwise manage records of the searching features 116 based on thereceived searching histories, searching statistics, and/or othersuitable information. For example, the collection component 122 cancompile most frequently searched keywords, frequencies of searchingrelated to the keywords, and/or other suitable information into recordsof searching features. In other examples, the collection component 122can also collect interactions of the members 101 (FIG. 1) and compilesuch information into records of searching features related toindividual members 101. Example schemas suitable for the searchingfeatures 116 are described below in more detail with reference to FIGS.4A and 4B.

The search component 124 can be configured to determine a search list140 of content servers 110 and/or corresponding distributed indices 118based on the searching features 116 in response to the received searchquery 138 and optionally the member profile 113. For example, the searchcomponent 124 can determine that the search list 140 includesidentifications of content servers 118 hosting content items 110 of asub-organization (e.g., “engineering department”) of the member 101. Inother examples, the search component 124 can determine that the searchlist 140 can include those most searched in the organization, asub-organization of the organization, or a group of other members themember interacts most with. Upon determining the search list 140, thesearch component 124 can return the search list 140 to the search engine106 (FIG. 1).

FIGS. 4A-4B are example data schemas suitable for records of searchingfeatures 116 in accordance with embodiments of the disclosed technology.As shown in FIG. 4A, a schema 160 for a record of searching features 116can include an ID field 161, an email address field 162, a top keywordfield 163, a query history field 164, a visits field 165, an activityfield 165, and an interaction field 166.

The ID field 161 can be configured to contain an identification of anorganization or sub-organization. The email address field 162 can beconfigured to contain an email address of the organization orsub-organization. The top keyword field 163 can be configured to containtop keyword(s) searched in the organization or sub-organization. Thequery history field 164 can be configured to contain searching historyof the organization or sub-organization. The visits field 165 can beconfigured to contain identifications of members 101 who have visitedthe organization or sub-organization. The activity field 165 can beconfigured to contain statistics of activities (e.g., number of emailssent) in the organization or sub-organization. The interaction field 166can be configured to contain data indicating interactions (e.g., likes)or statistics thereof in the organization or sub-organization. Thefollowing is an example record of the searching features 116 in theillustrated schema:

ID {91A08A55-A853-4A9A-8BF9-28DDF30A0FB6} Email Address group1@xyz.comTop Keyword [“Cloud”, “Store”, “Apps”, “Updates”] Query History[“Windows 10”,“Redstone”,“Apps”} Visits{“Key”:{“DateUtc”:“VDate(1448928000000+0000)V”}, “Value”:456} Activity[{“Key”:{“DateUtc”:“VDate(1448928000000+0000)V”}, “Value”:75}]Interactions [{“Key”:{“DateUtc”:“VDate(1448928000000+0000)V”},“Value”:47}]

FIG. 4B shows another suitable data schema 170 for the searchingfeatures 116. As shown in FIG. 4B, a record of searching features 116can include an ID field 171, an email address field 172, an organizationhierarchy field 173, an interaction field 174, and a visits field 175.The ID field 171 can be configured to contain an identification of agroup of members 101 (FIG. 1) or individual members 101. The emailaddress field 172 can be configured to contain an email address of agroup of members 101 or individual members 101. The organizationhierarchy field 173 can be configured to contain an organizationalposition of the group of members 101 or the individual members 101. Theinteraction field 174 can be configured to contain interaction historiesof the group of members 101 or the individual members 101. The visitsfield 175 can be configured to contain content items 110 visited by thegroup of members 101 or the individual members 101. The following is anexample record of the searching features 116 in the illustrated schema:

ID {91A08A55-A853-4A9A-8BF9-28DDF30A0FB6} Email Address member1@xyz.comOrganizational [{“Key”:0,“Value”:1},{“Key”:1,“Value”:1},{“Key”:2,Hierarchy “Value”:11}] Interaction[{“Key”:{“DateUtc”:“VDate(1448928000000+0000)V”}, “Value”:47}] Visits[{“Key”:{“DateUtc”:“VDate(1456790400000+0000)V”}, “Value”:20}]

FIG. 5A is a flowchart illustrating a process 200 of providingdistributed index searching in accordance with embodiments of thedisclosed technology. Even though embodiments of the process 200 aredescribed in the context of the computing system 100, in otherembodiments, the process 200 can also be implemented in computingsystems with additional and/or different components.

As shown in FIG. 5A, the process 200 can include receiving a searchquery from a member at stage 202. In certain embodiments, the searchquery can include one or more search terms. In other embodiments, thesearch query can also include an identification of the member,identification of a client device or software application used by themember, or other suitable information.

Upon receiving the search query, the process 200 can include determininga subset of distributed indices to search based on the search terms inthe received search query at stage 204. In certain embodiments, thesubset of distributed indices can be determined not based on a masterindex of the distributed indices but rather records of searchingfeatures collected from individual content servers 118 (FIG. 1). Thesearching features can include data or data records representing contentsearching or interaction profiles related to an organization orindividual members of the organization. For example, the searchingfeatures can include top keywords searched, query history, amount ofsearching of an organization, sub-organization, groups of members, orindividual members of the organization. In another example, thesearching features can also include interaction history, for instance,emails sent, comments received, or other suitable types of interactionsbetween groups of members or individual members of the organization. Incertain embodiments, the foregoing determination can be performed on aserver at which the search query is received. In other embodiments, theforegoing determination can be at least partially performed by adatabase server containing records of the searching features. The serverat which the search query is received can optionally supplement, remove,or otherwise modify the determined subset of distributed indices.Examples operations of such determination are described in more detailbelow with reference to FIG. 5B.

The process 200 can then include transmitting search requests to contentservers 118 hosting the subset of distributed indices at stage 206. Incertain embodiments, the search requests can include the search terms inthe received search query. In other embodiments, the search requests canalso include data representing a member profile or other suitableinformation. The process 200 can then include receiving and processingsearch results at stage 208. In certain embodiments, the search resultsreceived from the content servers can be aggregated. In otherembodiments, the search results can be sorted, filtered, ranked, orotherwise processed. The process 200 can then include outputting theaggregated search results to the member in response to the receivedsearch query at stage 210.

FIG. 5B is a flowchart illustrating operations suitable for determininga subset of distributed indices in accordance with embodiments of thedisclosed technology. As shown in FIG. 5B, the operations can includetransmitting a search query and optionally member profile information toa database server containing records of searching features collectedfrom individual content servers 118 (FIG. 1). The operations can theninclude receiving a list of distributed indices to be searched from thedatabase server at stage 214. Optionally, the operations can alsoinclude modifying the list of distributed indices by, for example,supplementing, subtracting, or otherwise adjusting items in the list ofdistributed indices at stage 216.

FIG. 6 is a flowchart illustrating a process 220 of compiling a databaseof searching features in accordance with embodiments of the disclosedtechnology. As shown in FIG. 6, the process 220 can include collectingsearching features at stage 222. In certain embodiments, a crawler canbe used to collect the searching features from the content servers 118(FIG. 1). In other embodiments, the searching features can be collectedvia reporting by the content servers 118 or other suitable techniques.The process 220 can then include updating searching feature records atstage 224. In certain embodiments, entries in the searching featurerecords can be revised, created, deleted, or otherwise changed. In otherembodiments, new searching feature records may be created. The process220 can then include a decision stage 226 to determine whether a timelapse since last update exceeds a preset threshold (e.g., 1 day or othersuitable periods). In response to determining that the time lapse sincelast update exceeds the preset threshold, the process 220 can revert tocollecting searching features at stage 222. Otherwise, the process 220continues to monitor for the time lapse.

FIG. 7 is a computing device 300 suitable for certain components of thecomputing system 100 in FIG. 1. For example, the computing device 300can be suitable for the search engine 106, the feature tracker 112, orthe content servers 118 of FIG. 1. In a very basic configuration 302,the computing device 300 can include one or more processors 304 and asystem memory 306. A memory bus 308 can be used for communicatingbetween processor 304 and system memory 306.

Depending on the desired configuration, the processor 304 can be of anytype including but not limited to a microprocessor (μP), amicrocontroller (μC), a digital signal processor (DSP), or anycombination thereof. The processor 304 can include one more levels ofcaching, such as a level-one cache 310 and a level-two cache 312, aprocessor core 314, and registers 316. An example processor core 314 caninclude an arithmetic logic unit (ALU), a floating-point unit (FPU), adigital signal processing core (DSP Core), or any combination thereof.An example memory controller 318 can also be used with processor 304, orin some implementations memory controller 318 can be an internal part ofprocessor 304.

Depending on the desired configuration, the system memory 306 can be ofany type including but not limited to volatile memory (such as RAM),non-volatile memory (such as ROM, flash memory, etc.) or any combinationthereof. The system memory 306 can include an operating system 320, oneor more applications 322, and program data 324. This described basicconfiguration 302 is illustrated in FIG. 7 by those components withinthe inner dashed line.

The computing device 300 can have additional features or functionality,and additional interfaces to facilitate communications between basicconfiguration 302 and any other devices and interfaces. For example, abus/interface controller 330 can be used to facilitate communicationsbetween the basic configuration 302 and one or more data storage devices332 via a storage interface bus 334. The data storage devices 332 can beremovable storage devices 336, non-removable storage devices 338, or acombination thereof. Examples of removable storage and non-removablestorage devices include magnetic disk devices such as flexible diskdrives and hard-disk drives (HDD), optical disk drives such as compactdisk (CD) drives or digital versatile disk (DVD) drives, solid statedrives (SSD), and tape drives to name a few. Example computer storagemedia can include volatile and nonvolatile, removable and non-removablemedia implemented in any method or technology for storage ofinformation, such as computer readable instructions, data structures,program modules, or other data. The term “computer readable storagemedia” or “computer readable storage device” excludes propagated signalsand communication media.

The system memory 306, removable storage devices 336, and non-removablestorage devices 338 are examples of computer readable storage media.Computer readable storage media include, but not limited to, RAM, ROM,EEPROM, flash memory or other memory technology, CD-ROM, digitalversatile disks (DVD) or other optical storage, magnetic cassettes,magnetic tape, magnetic disk storage or other magnetic storage devices,or any other media which can be used to store the desired informationand which can be accessed by computing device 300. Any such computerreadable storage media can be a part of computing device 300. The term“computer readable storage medium” excludes propagated signals andcommunication media.

The computing device 300 can also include an interface bus 340 forfacilitating communication from various interface devices (e.g., outputdevices 342, peripheral interfaces 344, and communication devices 346)to the basic configuration 302 via bus/interface controller 330. Exampleoutput devices 342 include a graphics processing unit 348 and an audioprocessing unit 350, which can be configured to communicate to variousexternal devices such as a display or speakers via one or more A/V ports352. Example peripheral interfaces 344 include a serial interfacecontroller 354 or a parallel interface controller 356, which can beconfigured to communicate with external devices such as input devices(e.g., keyboard, mouse, pen, voice input device, touch input device,etc.) or other peripheral devices (e.g., printer, scanner, etc.) via oneor more I/O ports 358. An example communication device 346 includes anetwork controller 360, which can be arranged to facilitatecommunications with one or more other computing devices 362 over anetwork communication link via one or more communication ports 364.

The network communication link can be one example of a communicationmedia. Communication media can typically be embodied by computerreadable instructions, data structures, program modules, or other datain a modulated data signal, such as a carrier wave or other transportmechanism, and can include any information delivery media. A “modulateddata signal” can be a signal that has one or more of its characteristicsset or changed in such a manner as to encode information in the signal.By way of example, and not limitation, communication media can includewired media such as a wired network or direct-wired connection, andwireless media such as acoustic, radio frequency (RF), microwave,infrared (IR) and other wireless media. The term computer readable mediaas used herein can include both storage media and communication media.

The computing device 300 can be implemented as a portion of a small-formfactor portable (or mobile) electronic device such as a cell phone, apersonal data assistant (PDA), a personal media player device, awireless web-watch device, a personal headset device, an applicationspecific device, or a hybrid device that include any of the abovefunctions. The computing device 300 can also be implemented as apersonal computer including both laptop computer and non-laptop computerconfigurations.

Specific embodiments of the technology have been described above forpurposes of illustration. However, various modifications can be madewithout deviating from the foregoing disclosure. In addition, many ofthe elements of one embodiment can be combined with other embodiments inaddition to or in lieu of the elements of the other embodiments.Accordingly, the technology is not limited except as by the appendedclaims.

I/We claim:
 1. A method for providing distributed index searching in acomputer system accessible to members via a computer network, thecomputer system including a set of content servers individually hostingcorresponding content items and a distributed index of the contentitems, the method comprising: receiving, at a server, a search query forcontent from a member via the computer network, the search querycontaining search terms; and in response to receiving the search query,at the server, transmitting the search terms to a database servercontaining records of searching features related to the computer system,the records of searching features containing information of contentsearching profiles of an organization, a sub-organization, or theindividual members of the organization; receiving, from the databaseserver, a list of distributed indices determined by the database serverbased on the search terms and the records of searching features;transmitting, via the computer network, search requests to a subset ofthe content servers corresponding to the distributed indices in thelist, the search requests requesting the content servers to searchcorresponding distributed indices based on the search terms; andreceiving sets of search results from the subset of content servers, thesearch results identifying content items hosted on the correspondingcontent servers relevant to the search terms.
 2. The method of claim 1,further comprising: aggregating the received sets of search results fromthe content servers; and providing, via the computer network, theaggregated search results to the member in response to receiving thesearch query.
 3. The method of claim 1, further comprising: transmittingdata representing a member profile of the member along with the searchterms in the search query to the database server; and wherein the listof distributed indices to be searched are determined by the databaseserver based on a combination of the search terms, the data representingthe member profile, and the searching features.
 4. The method of claim 1wherein the records of the searching features contain data representingat least one of top keywords searched, a query history, statistics ofactivities, or interactions in the organization or the sub-organization.5. The method of claim 1 wherein the records of the searching featurescontain data representing at least one of an organizational hierarchy oran interaction of the member with other members in the organization. 6.The method of claim 1 wherein the database server does not contain amaster index of the distributed indices hosted on the correspondingcontent servers.
 7. The method of claim 1, further comprisingsupplementing the received list of distributed indices at the serverbefore transmitting, via the computer network, the search requests tothe subset of the content servers.
 8. A method for providing distributedindex searching in a computer system accessible to members via acomputer network, the computer system including content items hosted oncontent servers and a set of distributed indices of a subset of thecontent items hosted on a corresponding content server, the methodcomprising: receiving, at the database server and via the computernetwork, search terms included in a search query for content from amember; and in response to receiving the search terms, at the databaseserver, determining a subset of the distributed indices to be searchedin response to the search query based on the received search terms andone or more records of searching features on the database server, thesearching features containing data representing content searchingprofiles of at least one of an organization or the individual members ofthe organization; and providing, from the database server and via thecomputer network, the determined list of distributed indices to besearched based on the search terms in the search query.
 9. The method ofclaim 8, further comprising providing, from the database server and viathe computer network, a subset of the content servers corresponding tothe distributed indices in the determined list in response to receivingthe search terms.
 10. The method of claim 8 wherein: the searchingfeatures include data representing keywords searched in theorganization; and the determined subset of indices include one or moredistributed indices that have been searched based on the keywords. 11.The method of claim 8 wherein: the searching features include datarepresenting query history containing terms searched in theorganization; and the determined subset of indices include one or moredistributed indices that have been searched based on the terms in thequery history.
 12. The method of claim 8 wherein: the searching featuresinclude data representing documents visited in the organization; and thedetermined subset of indices include one or more distributed indicesthat correspond to the visited documents.
 13. The method of claim 8wherein: the searching features include data representing anorganizational hierarchy of the member; and the determined subset ofindices include one or more distributed indices that correspond to asub-organization the member belongs determined based on theorganizational hierarchy of the member.
 14. The method of claim 8wherein the database server does not contain a master index of thedistributed indices hosted on the corresponding content servers.
 15. Acomputing device for providing distributed index searching in a computersystem accessible to members via a computer network, the computer systemincluding a set of content servers individually hosting correspondingcontent items and a distributed index of the content items, thecomputing device comprising: a processor; and a memory operativelycoupled to the processor, the memory containing instructions executableby the processor to cause the processor to: in response to receiving asearch query for content from a member via the computer network,determine, from the database server, a list of distributed indices basedon the search terms and records of searching features related to thecomputer system, the records of searching features containinginformation of content searching profiles of an organization or theindividual members of the organization; transmit, via the computernetwork, search requests to a subset of the content serverscorresponding to the distributed indices in the list, the searchrequests requesting the content servers to search correspondingdistributed indices based on the search terms; and receive sets ofsearch results from the subset of content servers, the search resultsidentifying content items hosted on the corresponding content serversrelevant to the search terms.
 16. The computing device of claim 15wherein the memory contains instructions executable to cause theprocessor to: aggregate the received sets of search results from thecontent servers; and provide, via the computer network, the aggregatedsearch results to the member in response to receiving the search query.17. The computing device of claim 15 wherein the memory containsinstructions executable to cause the processor to: retrieve datarepresenting a member profile of the member along with the search termsin the search query; and wherein the list of distributed indices to besearched are determined by the database server based on a combination ofthe search terms, the data representing the member profile, and thesearching features.
 18. The computing device of claim 15 wherein therecords of the searching features contain data representing at least oneof top keywords searched or a query history of the organization or themember.
 19. The computing device of claim 15 wherein the records of thesearching features contain data representing at least one of anorganizational hierarchy or an interaction of the member with othermembers in the organization.
 20. The computing device of claim 15wherein the memory contains instructions executable to cause theprocessor to supplement the received list of distributed indices at theserver before transmitting, via the computer network, the searchrequests to the subset of the content servers.